Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems

Capacity expansion models provide the basis on which to decide where, when, how much and what technology type to deploy. In systems with large shares of variable renewable energy, the low temporal detail of these models has been shown to introduce biases, prompting much recent work to reduce them. This paper shows that this issue is fairly secondary compared to the impact of maximum investment rates. Through this parameter, typically not discussed in capacity expansion studies, many notions can collectively be expressed, such as the rate at which capacity is financed, institutions approve development, manufacturers roll-out equipment, civil engineers build infrastructure, network operators connect plants etc. This paper shows that considering even ambitious development rates significantly increases total system costs, and drastically changes the structure of an optimal generation mix. The presented sensitivity analysis is based on a multi-region representation of the European power system, modelled using the open-source tool OSeMOSYS, to which a novel power transmission module has been added. Results stress the extent to which hopes of meeting climate targets hinge on society’s collective ability to deploy new low-carbon infrastructure fast enough. Energy policy can enhance this ability by providing long-term visibility and stability, reducing investment risk.